Real-time Global Illumination Decomposition of Videos

Author:

Meka Abhimitra1,Shafiei Mohammad2,Zollhöfer Michael3,Richardt Christian4,Theobalt Christian5

Affiliation:

1. Max Planck Institute for Informatics, Saarland Informatics Campus and Google

2. Max Planck Institute for Informatics, Saarland Informatics Campus

3. Stanford University, Pittsburgh, PA, United States of America

4. University of Bath, Claverton Down, Bath, UK

5. Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbruecken, Germany

Abstract

We propose the first approach for the decomposition of a monocular color video into direct and indirect illumination components in real time. We retrieve, in separate layers, the contribution made to the scene appearance by the scene reflectance, the light sources, and the reflections from various coherent scene regions to one another. Existing techniques that invert global light transport require image capture under multiplexed controlled lighting or only enable the decomposition of a single image at slow off-line frame rates. In contrast, our approach works for regular videos and produces temporally coherent decomposition layers at real-time frame rates. At the core of our approach are several sparsity priors that enable the estimation of the per-pixel direct and indirect illumination layers based on a small set of jointly estimated base reflectance colors. The resulting variational decomposition problem uses a new formulation based on sparse and dense sets of non-linear equations that we solve efficiently using a novel alternating data-parallel optimization strategy. We evaluate our approach qualitatively and quantitatively and show improvements over the state-of-the-art in this field, in both quality and runtime. In addition, we demonstrate various real-time appearance editing applications for videos with consistent illumination.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. IBL‐NeRF: Image‐Based Lighting Formulation of Neural Radiance Fields;Computer Graphics Forum;2023-10

2. Image vectorization and editing via linear gradient layer decomposition;ACM Transactions on Graphics;2023-07-26

3. All-photon Polarimetric Time-of-Flight Imaging;2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2022-06

4. OutCast: Outdoor Single‐image Relighting with Cast Shadows;Computer Graphics Forum;2022-05

5. Relighting4D: Neural Relightable Human from Videos;Lecture Notes in Computer Science;2022

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